Title :
Prosody dependent Mandarin speech recognition
Author :
Ni, Chong-Jia ; Liu, Wen-Ju ; Xu, Bo
fDate :
July 31 2011-Aug. 5 2011
Abstract :
In this paper, we discuss how to model and train Mandarin prosody dependent acoustic model based on automatic prosody annotation corpus. Based on prosody annotation corpus, we first utilize our proposed methods to train prosody dependent and prosody independent tonal syllable model, and then use these models to get the mixed acoustic models. In this paper, we also utilize tone model to improve the correct rate of tonal syllable through revising the tone of the tonal syllable at certain significant level. When compared with the baseline system, the performance of our proposed mixed speech recognition system improves the correct rate of tonal syllable significantly.
Keywords :
speech recognition; Mandarin prosody dependent acoustic model; automatic prosody annotation corpus; prosody dependent Mandarin speech recognition; prosody independent tonal syllable model; tone model; Acoustics; Hidden Markov models; Probability distribution; Speech; Speech recognition; Stress; Training;
Conference_Titel :
Neural Networks (IJCNN), The 2011 International Joint Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4244-9635-8
DOI :
10.1109/IJCNN.2011.6033221